Periodic digital signals are commonly used in a variety of electronic devices, such as dynamic random access memory (“DRAM”) and flash memory. These periodic digital signals are frequently produced as clocks within these devices, and are typically used to establish the timing of a digital signal, or the timing at which an operation is performed. Periodic digital signals may also be used as in a constant strobe signal. Data signals may be transmitted to or received from electronic devices in synchronism with a periodic digital signal. Precise alignment of the clock and data signals is of importance in order to permit accurate data transmission.
As the speed of memory and other electronic devices continues to increase, the “eye” (or period in which a digital signal is valid), becomes smaller. This requires higher clock precision in order to properly align the phases of a data eye with the clock, and increases the importance of the timing of the clock or strobe. The alignment of the data eye is critical in data recovery circuits in order to synchronize the internal or external clock with respect to the incoming data. The data in the channel can be delayed for a variety of reasons such as process variation, temperature, local voltage and mismatched physical trace lengths. Additionally, the growing trend to include several computing devices on the same board present another challenge with respect to synchronizing a clock with all components within a system. As a result, there may be a need to adjust the phase of a clock signal to synchronize it with any synchronous digital signal or synchronous system components.
In the past, this type of clock adjustment has been performed with mixer-based analog interpolators, which work by mixing two quadrature signals together with an analog mixer. With the use of digitally controlled current mirrors, the strength of each input can be adjusted to produce any arbitrary phase at the output. However, analog mixers have significant power and area costs. Additionally, analog mixers inherently produce a significant amount of integral non-linearity, which occurs when phase relationships do not change in a linear fashion. This non-linearity is often adjusted and accounted for through costly signal pre- and post-processing, however these methods are complicated and consume extra power and space.